通过体外计算和模拟研究高选择性磷酸二酯酶 5 和 6 抑制剂的机理

Lihang Qu, Kaijian Sun, Zhouyu Jiang, Ting Wang, Linlin Chen, Chunjian Shen, Ruidong Gu
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摘要

简介:在临床实践中,磷酸二酯酶 5 (PDE5) 抑制剂常用于治疗勃起功能障碍和肺动脉高压。然而,由于PDE5和磷酸二酯酶6(PDE6)在结构上高度相似,现有药物有可能会对PDE6产生脱靶效应,导致低视力和色盲等视觉障碍。以往关于 PDE5 抑制剂选择性的研究主要集中在西地那非和他达拉非等已上市药物上:本研究以一种高选择性的PDE5抑制剂配体3为研究对象,采用分子对接、分子动力学模拟、MM-GBSA、丙氨酸扫描和独立梯度模型分析等方法研究PDE5抑制剂选择性的生物学机制:本研究发现配体3与PDE5A和PDE6C靶点的结合模式明显不同。配体3与PDE5A结合时表现出更强的库仑力,而与PDE6C结合时则表现出更强的范德华力。与 PDE6C 相比,配体 3 与 PDE5A 的活性位点结合得更深,使其侧链能够有效地与关键的 TYR612 结合,而与 PDE6C 结合得较浅时,配体 3 则缺乏类似的作用。通过计算模拟研究高选择性抑制剂的机理可能会为药物的有效治疗提供启示。
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Mechanism investigation of highly selective inhibitors toward phosphodiesterase 5 and 6 via the in vitro calculation and simulation
Introduction: In clinical practice, phosphodiesterase 5 (PDE5) inhibitors are commonly used to treat erectile dysfunction and pulmonary arterial hypertension. However, due to the high structural similarity between PDE5 and Phosphodiesterase 6 (PDE6), there is a risk that existing drugs will cause off-target effects on PDE6 resulting in visual disorders such as low visual acuity and color blindness. Previous research on the selectivity of PDE5 inhibitors focused on marketed drugs such as sildenafil and tadalafil.Methods: In this study, a highly selective PDE5 inhibitor, ligand3, was used as the subject, and molecular docking, molecular dynamics simulations, MM-GBSA, alanine scanning, and independent gradient model analysis were employed to investigate the biological mechanism underlying the selectivity of PDE5 inhibitors.Results and Discussion: The present work revealed that the binding mode of ligand3 to the PDE5A and PDE6C targets was distinctly different. Ligand3 exhibited stronger coulombic forces when binding to PDE5A, while showing stronger van der waals forces when binding to PDE6C. Ligand3 binds more deeply at the active site of PDE5A than at PDE6C, allowing its side chains to effectively bind to the critical TYR612, whereas in the case of the shallow binding to PDE6C, ligand3 lacks a similar effect. Mechanism investigations of highly selective inhibitors through computational simulation might provide an insight into potent treatment of drugs.
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